Disadvantages of Tree Data Structure

  • Unbalanced Trees, meaning that the height of the tree is skewed towards one side, which can lead to inefficient search times.
  • Trees demand more memory space requirements than some other data structures like arrays and linked lists, especially if the tree is very large.
  • The implementation and manipulation of trees can be complex and require a good understanding of the algorithms.


Introduction to Tree Data Structure

Tree data structure is a specialized data structure to store data in hierarchical manner. It is used to organize and store data in the computer to be used more effectively. It consists of a central node, structural nodes, and sub-nodes, which are connected via edges. We can also say that tree data structure has roots, branches, and leaves connected.

Table of Content

  • What is Tree Data Structure?
  • Basic Terminologies In Tree Data Structure
  • Representation of Tree Data Structure
  • Importance for Tree Data Structure
  • Types of Tree data structures
  • Basic Operations Of Tree Data Structure
  • Implementation of Tree Data Structure
  • Properties of Tree Data Structure
  • Applications of Tree Data Structure
  • Advantages of Tree Data Structure
  • Disadvantages of Tree Data Structure

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What is Tree Data Structure?

Tree data structure is a hierarchical structure that is used to represent and organize data in a way that is easy to navigate and search. It is a collection of nodes that are connected by edges and has a hierarchical relationship between the nodes....

Basic Terminologies In Tree Data Structure:

Parent Node: The node which is a predecessor of a node is called the parent node of that node. {B} is the parent node of {D, E}.Child Node: The node which is the immediate successor of a node is called the child node of that node. Examples: {D, E} are the child nodes of {B}.Root Node: The topmost node of a tree or the node which does not have any parent node is called the root node. {A} is the root node of the tree. A non-empty tree must contain exactly one root node and exactly one path from the root to all other nodes of the tree.Leaf Node or External Node: The nodes which do not have any child nodes are called leaf nodes. {K, L, M, N, O, P, G} are the leaf nodes of the tree.Ancestor of a Node: Any predecessor nodes on the path of the root to that node are called Ancestors of that node. {A,B} are the ancestor nodes of the node {E}Descendant: A node x is a descendant of another node y if and only if y is an ancestor of x.Sibling: Children of the same parent node are called siblings. {D,E} are called siblings.Level of a node: The count of edges on the path from the root node to that node. The root node has level 0.Internal node: A node with at least one child is called Internal Node.Neighbour of a Node: Parent or child nodes of that node are called neighbors of that node.Subtree: Any node of the tree along with its descendant....

Representation of Tree Data Structure:

A tree consists of a root node, and zero or more subtrees T1, T2, … , Tk such that there is an edge from the root node of the tree to the root node of each subtree. Subtree of a node X consists of all the nodes which have node X as the ancestor node....

Importance for Tree Data Structure:

1. One reason to use trees might be because you want to store information that naturally forms a hierarchy. For example, the file system on a computer:...

Types of Tree data structures:

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Basic Operations Of Tree Data Structure:

Create – create a tree in the data structure.Insert − Inserts data in a tree.Search − Searches specific data in a tree to check whether it is present or not.Traversal:Depth-First-Search TraversalBreadth-First-Search Traversal...

Implementation of Tree Data Structure:

C++ // C++ program to demonstrate some of the above // terminologies #include using namespace std; // Function to add an edge between vertices x and y void addEdge(int x, int y, vector >& adj) { adj[x].push_back(y); adj[y].push_back(x); } // Function to print the parent of each node void printParents(int node, vector >& adj, int parent) { // current node is Root, thus, has no parent if (parent == 0) cout << node << "->Root" << endl; else cout << node << "->" << parent << endl; // Using DFS for (auto cur : adj[node]) if (cur != parent) printParents(cur, adj, node); } // Function to print the children of each node void printChildren(int Root, vector >& adj) { // Queue for the BFS queue q; // pushing the root q.push(Root); // visit array to keep track of nodes that have been // visited int vis[adj.size()] = { 0 }; // BFS while (!q.empty()) { int node = q.front(); q.pop(); vis[node] = 1; cout << node << "-> "; for (auto cur : adj[node]) if (vis[cur] == 0) { cout << cur << " "; q.push(cur); } cout << endl; } } // Function to print the leaf nodes void printLeafNodes(int Root, vector >& adj) { // Leaf nodes have only one edge and are not the root for (int i = 1; i < adj.size(); i++) if (adj[i].size() == 1 && i != Root) cout << i << " "; cout << endl; } // Function to print the degrees of each node void printDegrees(int Root, vector >& adj) { for (int i = 1; i < adj.size(); i++) { cout << i << ": "; // Root has no parent, thus, its degree is equal to // the edges it is connected to if (i == Root) cout << adj[i].size() << endl; else cout << adj[i].size() - 1 << endl; } } // Driver code int main() { // Number of nodes int N = 7, Root = 1; // Adjacency list to store the tree vector > adj(N + 1, vector()); // Creating the tree addEdge(1, 2, adj); addEdge(1, 3, adj); addEdge(1, 4, adj); addEdge(2, 5, adj); addEdge(2, 6, adj); addEdge(4, 7, adj); // Printing the parents of each node cout << "The parents of each node are:" << endl; printParents(Root, adj, 0); // Printing the children of each node cout << "The children of each node are:" << endl; printChildren(Root, adj); // Printing the leaf nodes in the tree cout << "The leaf nodes of the tree are:" << endl; printLeafNodes(Root, adj); // Printing the degrees of each node cout << "The degrees of each node are:" << endl; printDegrees(Root, adj); return 0; } Java // java code for above approach import java.io.*; import java.util.*; class GFG { // Function to print the parent of each node public static void printParents(int node, Vector > adj, int parent) { // current node is Root, thus, has no parent if (parent == 0) System.out.println(node + "->Root"); else System.out.println(node + "->" + parent); // Using DFS for (int i = 0; i < adj.get(node).size(); i++) if (adj.get(node).get(i) != parent) printParents(adj.get(node).get(i), adj, node); } // Function to print the children of each node public static void printChildren(int Root, Vector > adj) { // Queue for the BFS Queue q = new LinkedList<>(); // pushing the root q.add(Root); // visit array to keep track of nodes that have been // visited int vis[] = new int[adj.size()]; Arrays.fill(vis, 0); // BFS while (q.size() != 0) { int node = q.peek(); q.remove(); vis[node] = 1; System.out.print(node + "-> "); for (int i = 0; i < adj.get(node).size(); i++) { if (vis[adj.get(node).get(i)] == 0) { System.out.print(adj.get(node).get(i) + " "); q.add(adj.get(node).get(i)); } } System.out.println(); } } // Function to print the leaf nodes public static void printLeafNodes(int Root, Vector > adj) { // Leaf nodes have only one edge and are not the // root for (int i = 1; i < adj.size(); i++) if (adj.get(i).size() == 1 && i != Root) System.out.print(i + " "); System.out.println(); } // Function to print the degrees of each node public static void printDegrees(int Root, Vector > adj) { for (int i = 1; i < adj.size(); i++) { System.out.print(i + ": "); // Root has no parent, thus, its degree is // equal to the edges it is connected to if (i == Root) System.out.println(adj.get(i).size()); else System.out.println(adj.get(i).size() - 1); } } // Driver code public static void main(String[] args) { // Number of nodes int N = 7, Root = 1; // Adjacency list to store the tree Vector > adj = new Vector >(); for (int i = 0; i < N + 1; i++) { adj.add(new Vector()); } // Creating the tree adj.get(1).add(2); adj.get(2).add(1); adj.get(1).add(3); adj.get(3).add(1); adj.get(1).add(4); adj.get(4).add(1); adj.get(2).add(5); adj.get(5).add(2); adj.get(2).add(6); adj.get(6).add(2); adj.get(4).add(7); adj.get(7).add(4); // Printing the parents of each node System.out.println("The parents of each node are:"); printParents(Root, adj, 0); // Printing the children of each node System.out.println( "The children of each node are:"); printChildren(Root, adj); // Printing the leaf nodes in the tree System.out.println( "The leaf nodes of the tree are:"); printLeafNodes(Root, adj); // Printing the degrees of each node System.out.println("The degrees of each node are:"); printDegrees(Root, adj); } } // This code is contributed by rj13to. Python from collections import deque # Function to add an edge between vertices x and y def addEdge(x, y, adj): adj[x].append(y) adj[y].append(x) # Function to print the parent of each node def printParents(node, adj, parent): # current node is Root, thus, has no parent if parent == 0: print("{}->Root".format(node)) else: print("{}->{}".format(node, parent)) # Using DFS for cur in adj[node]: if cur != parent: printParents(cur, adj, node) # Function to print the children of each node def printChildren(Root, adj): # Queue for the BFS q = deque() # pushing the root q.append(Root) # visit array to keep track of nodes that have been # visited vis = [0] * len(adj) # BFS while q: node = q.popleft() vis[node] = 1 print("{}->".format(node)), for cur in adj[node]: if vis[cur] == 0: print(cur), q.append(cur) print() # Function to print the leaf nodes def printLeafNodes(Root, adj): # Leaf nodes have only one edge and are not the root for i in range(1, len(adj)): if len(adj[i]) == 1 and i != Root: print(i), # Function to print the degrees of each node def printDegrees(Root, adj): for i in range(1, len(adj)): print(i, ":"), # Root has no parent, thus, its degree is equal to # the edges it is connected to if i == Root: print(len(adj[i])) else: print(len(adj[i]) - 1) # Driver code N = 7 Root = 1 # Adjacency list to store the tree adj = [[] for _ in range(N + 1)] # Creating the tree addEdge(1, 2, adj) addEdge(1, 3, adj) addEdge(1, 4, adj) addEdge(2, 5, adj) addEdge(2, 6, adj) addEdge(4, 7, adj) # Printing the parents of each node print("The parents of each node are:") printParents(Root, adj, 0) # Printing the children of each node print("The children of each node are:") printChildren(Root, adj) # Printing the leaf nodes in the tree print("The leaf nodes of the tree are:") printLeafNodes(Root, adj) # Printing the degrees of each node print("The degrees of each node are:") printDegrees(Root, adj) C# using System; using System.Collections.Generic; class Program { static void PrintParents(int node, List> adj, int parent) { if (parent == 0) { Console.WriteLine($"{node} -> Root"); } else { Console.WriteLine($"{node} -> {parent}"); } foreach (int cur in adj[node]) { if (cur != parent) { PrintParents(cur, adj, node); } } } static void PrintChildren(int Root, List> adj) { Queue q = new Queue(); q.Enqueue(Root); bool[] vis = new bool[adj.Count]; while (q.Count > 0) { int node = q.Dequeue(); vis[node] = true; Console.Write($"{node} -> "); foreach (int cur in adj[node]) { if (!vis[cur]) { Console.Write($"{cur} "); q.Enqueue(cur); } } Console.WriteLine(); } } static void PrintLeafNodes(int Root, List> adj) { for (int i = 0; i < adj.Count; i++) { if (adj[i].Count == 1 && i != Root) { Console.Write($"{i} "); } } Console.WriteLine(); } static void PrintDegrees(int Root, List> adj) { for (int i = 1; i < adj.Count; i++) { Console.Write($"{i}: "); if (i == Root) { Console.WriteLine(adj[i].Count); } else { Console.WriteLine(adj[i].Count - 1); } } } static void Main(string[] args) { int N = 7; int Root = 1; List> adj = new List>(); for (int i = 0; i <= N; i++) { adj.Add(new List()); } adj[1].AddRange(new int[] { 2, 3, 4 }); adj[2].AddRange(new int[] { 1, 5, 6 }); adj[4].Add(7); Console.WriteLine("The parents of each node are:"); PrintParents(Root, adj, 0); Console.WriteLine("The children of each node are:"); PrintChildren(Root, adj); Console.WriteLine("The leaf nodes of the tree are:"); PrintLeafNodes(Root, adj); Console.WriteLine("The degrees of each node are:"); PrintDegrees(Root, adj); } } JavaScript // Number of nodes let N = 7, Root = 1; // Adjacency list to store the tree let adj = new Array(N + 1).fill(null).map(() => []); // Creating the tree addEdge(1, 2, adj); addEdge(1, 3, adj); addEdge(1, 4, adj); addEdge(2, 5, adj); addEdge(2, 6, adj); addEdge(4, 7, adj); // Function to add an edge between vertices x and y function addEdge(x, y, arr) { arr[x].push(y); arr[y].push(x); } // Function to print the parent of each node function printParents(node, arr, parent) { // current node is Root, thus, has no parent if (parent == 0) console.log(`${node}->Root`); else console.log(`${node}->${parent}`); // Using DFS for (let cur of arr[node]) if (cur != parent) printParents(cur, arr, node); } // Function to print the children of each node function printChildren(Root, arr) { // Queue for the BFS let q = []; // pushing the root q.push(Root); // visit array to keep track of nodes that have been // visited let vis = new Array(arr.length).fill(0); // BFS while (q.length > 0) { let node = q.shift(); vis[node] = 1; console.log(`${node}-> `); for (let cur of arr[node]) if (vis[cur] == 0) { console.log(cur + " "); q.push(cur); } console.log("\n"); } } // Function to print the leaf nodes function printLeafNodes(Root, arr) { // Leaf nodes have only one edge and are not the root for (let i = 1; i < arr.length; i++) if (arr[i].length == 1 && i != Root) console.log(i + " "); console.log("\n"); } // Function to print the degrees of each node function printDegrees(Root, arr) { for (let i = 1; i < arr.length; i++) { console.log(`${i}: `); // Root has no parent, thus, its degree is equal to // the edges it is connected to if (i == Root) console.log(arr[i].length + "\n"); else console.log(arr[i].length - 1 + "\n"); } } // Driver code // Printing the parents of each node console.log("The parents of each node are:"); printParents(Root, adj, 0); // Printing the children of each node console.log("The children of each node are:"); printChildren(Root, adj); // Printing the leaf nodes in the tree console.log("The leaf nodes of the tree are:"); printLeafNodes(Root, adj); // Printing the degrees of each node console.log("The degrees of each node are:"); printDegrees(Root, adj); // This code is contributed by ruchikabaslas....

Properties of Tree Data Structure:

Number of edges: An edge can be defined as the connection between two nodes. If a tree has N nodes then it will have (N-1) edges. There is only one path from each node to any other node of the tree.Depth of a node: The depth of a node is defined as the length of the path from the root to that node. Each edge adds 1 unit of length to the path. So, it can also be defined as the number of edges in the path from the root of the tree to the node.Height of a node: The height of a node can be defined as the length of the longest path from the node to a leaf node of the tree.Height of the Tree: The height of a tree is the length of the longest path from the root of the tree to a leaf node of the tree.Degree of a Node: The total count of subtrees attached to that node is called the degree of the node. The degree of a leaf node must be 0. The degree of a tree is the maximum degree of a node among all the nodes in the tree....

Applications of Tree Data Structure:

File System:  This allows for efficient navigation and organization of files.Data Compression: Huffman coding is a popular technique for data compression that involves constructing a binary tree where the leaves represent characters and their frequency of occurrence. The resulting tree is used to encode the data in a way that minimizes the amount of storage required.Compiler Design: In compiler design, a syntax tree is used to represent the structure of a program. Database Indexing: B-trees and other tree structures are used in database indexing to efficiently search for and retrieve data....

Advantages of Tree Data Structure:

Tree offer Efficient Searching Depending on the type of tree, with average search times of O(log n) for balanced trees like AVL. Trees provide a hierarchical representation of data, making it easy to organize and navigate large amounts of information.The recursive nature of trees makes them easy to traverse and manipulate using recursive algorithms....

Disadvantages of Tree Data Structure:

Unbalanced Trees, meaning that the height of the tree is skewed towards one side, which can lead to inefficient search times.Trees demand more memory space requirements than some other data structures like arrays and linked lists, especially if the tree is very large.The implementation and manipulation of trees can be complex and require a good understanding of the algorithms....

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